AI investment surged to $252.3 billion in 2024, up 44.5% from the previous year, as companies rushed to capitalize on the technology’s promise. But this massive expansion is increasingly fueled by debt at a time when borrowing costs haven’t come down.
Oracle (ORCL) alone needs to borrow an estimated $25 billion annually to fulfill its OpenAI contracts. CoreWeave (CRWV), Nebius (NBIS), and other AI infrastructure companies are taking on billions in creative financing deals. With the AI market expected to reach $1.81 trillion by 2030, the question is whether these debt-laden bets will pay off.
As companies burn through cash faster than they generate revenue, experts are drawing uncomfortable parallels to past tech bubbles. Here’s what the mounting debt means for AI companies and the broader economy.
Rising Borrowing Costs Create Challenges
The AI boom’s debt dependency is creating unprecedented financial pressure. Oracle’s $82 billion debt load means that for every dollar Oracle owns, it owes $4.50 to lenders. For comparison, Google’s parent Alphabet Inc. (GOOGL) has a debt-to-equity ratio (D/E) of just 11.5%, or 11 cents for every dollar it’s worth.
“As borrowing costs rise due to higher interest rates, these companies face higher expenses to finance their growth,” Dave Kantaros, co-chair for AI at Foley’s Innovative Technology, told Investopedia. This means more money goes to paying off debt instead of funding operations or new projects.
That puts a lot of pressure on OpenAI, a major client for these companies. To justify all this spending, the company would need to grow its revenue from today’s $12 billion to $300 billion by 2030, a 2,400% increase.
Risks for the Wider Economy
Companies relying on loans or venture capital are feeling the pinch and may need to find ways to become profitable faster. “Elevated valuations are boosting consumption and investment. But if the AI bubble bursts, it could lead to recession and higher unemployment, similar to the early 2000s tech bust,” noted Natasha Allen, co-chair of venture capital at Foley.
Recent growth has mainly benefited wealthy households, while wage gains have lagged inflation. “Like the dot-com era, today’s AI boom sees a few tech giants dominating investment and investor excitement running high. But unlike many dot-com companies that failed to turn profits, many AI firms are already making money and serving practical needs in many industries,” Allen said. This means any correction in AI investment might cause less severe damage overall.
Also, AI jobs and technologies are more spread out geographically, reducing the risk of local economic shocks. This broader foundation and stronger profitability suggest the AI wave is hopefully on sturdier ground than the fragile bubble economy of the late 1990s.
What Investors and Companies Should Know
For everyday investors, the AI boom has meant significant gains in portfolios holding shares in an S&P 500 index fund, where just five AI-related companies now make up about 30% of their total value. AI has driven much of the market’s gains in 2025, but this concentration increases the risk to a portfolio should the AI boom falter.
Kantaros noted that investment is flowing primarily to established giants like Nvidia (NVDA) and OpenAI, while smaller AI companies struggle to secure funding. This winner-take-all dynamic means picking individual AI stocks has become extremely risky—even companies with promising technology may run out of cash before becoming profitable.
The Bottom Line
AI investment is booming, but borrowing costs are rising too, creating financial pressure. While the current situation has certain echoes of the dot-com bubble, the AI market is more mature and widely adopted, which may limit the fallout if a correction occurs.